Description Usage Arguments Value Examples
Node score (degree, betweenness, closenness, eigenvector centralities or clustering coefficient) for each network analysed.
1 2 3 4 5 6 7 8 9 10 11 | degreeCentrality(expr, labels, adjacencyMatrix)
betweennessCentrality(expr, labels, adjacencyMatrix)
betweennessEdgesCentrality(expr, labels, adjacencyMatrix)
closenessCentrality(expr, labels, adjacencyMatrix)
eigenvectorCentrality(expr, labels, adjacencyMatrix)
clusteringCoefficient(expr, labels, adjacencyMatrix)
|
expr |
Matrix of variables (columns) vs samples (rows). |
labels |
a vector in which a position indicates the phenotype of the corresponding sample or state. |
adjacencyMatrix |
a function that returns the adjacency matrix for a given variables values matrix. |
a list of vector containing the node scores (degree, betweenness, closenness, eigenvector centralities or clustering coefficient) of each network.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | set.seed(1)
expr <- as.data.frame(matrix(rnorm(120),40,30))
labels<-data.frame(code=rep(0:3,10),names=rep(c("A","B","C","D"),10))
adjacencyMatrix1 <- adjacencyMatrix(method="spearman", association="pvalue",
threshold="fdr", thr.value=0.05, weighted=FALSE)
# Degree centrality
degreeCentrality(expr, labels, adjacencyMatrix1)
# Betweenness Centrality
betweennessCentrality(expr, labels, adjacencyMatrix1)
# Edges Betweenness Centrality
betweennessEdgesCentrality(expr, labels, adjacencyMatrix1)
# Closenness Caentrality
closenessCentrality(expr, labels, adjacencyMatrix1)
# Eigenvector centrality
eigenvectorCentrality(expr, labels, adjacencyMatrix1)
# Clustering coefficient
clusteringCoefficient(expr, labels, adjacencyMatrix1)
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